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DBMS > Amazon DocumentDB vs. Amazon Neptune vs. Apache Druid vs. LMDB vs. Quasardb

System Properties Comparison Amazon DocumentDB vs. Amazon Neptune vs. Apache Druid vs. LMDB vs. Quasardb

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonApache Druid  Xexclude from comparisonLMDB  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceFast, reliable graph database built for the cloudOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA high performant, light-weight, embedded key-value database libraryDistributed, high-performance timeseries database
Primary database modelDocument storeGraph DBMS
RDF store
Relational DBMS
Time Series DBMS
Key-value storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score2.20
Rank#119  Overall
#9  Graph DBMS
#5  RDF stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websiteaws.amazon.com/­documentdbaws.amazon.com/­neptunedruid.apache.orgwww.symas.com/­symas-embedded-database-lmdbquasar.ai
Technical documentationaws.amazon.com/­documentdb/­resourcesaws.amazon.com/­neptune/­developer-resourcesdruid.apache.org/­docs/­latest/­designwww.lmdb.tech/­docdoc.quasar.ai/­master
DeveloperAmazonApache Software Foundation and contributorsSymasquasardb
Initial release20192017201220112009
Current release29.0.1, April 20240.9.32, January 20243.14.1, January 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache license v2Open Sourcecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++
Server operating systemshostedhostedLinux
OS X
Unix
Linux
Unix
Windows
BSD
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infoschema-less columns are supportedschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonononono
Secondary indexesyesnoyesnoyes infowith tags
SQL infoSupport of SQLnonoSQL for queryingnoSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
RESTful HTTP/JSON API
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnonononono
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infomanual/auto, time-basednoneSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.yes, via HDFS, S3 or other storage enginesnoneSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient mode
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoCryptographically strong user authentication and audit trail

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More resources
Amazon DocumentDBAmazon NeptuneApache DruidLMDBQuasardb
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